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Severe Acute Respiratory Syndrome Coronavirus 2 Related Diseases (COVID-19) is now one of the most challenging and concerning epidemics, which has been affecting the world so much. After that, countries around the world have been actively developing vaccines to deal with the sudden disease. How to carry out more efficient epidemic prevention has also become a problem of our concern. Unlike traditional SIR disease transmission models, network percolation has unique advantages in disease immune modelling, which makes it closer to reality in the simulation. This article introduces the study of SIR percolation network on infection probabilities of COVID-19, and proposes a method to preventing the spread of disease. © 2022 IEEE.
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Patients with cancer are at high risk for coronavirus disease 2019 (COVID-19). Institutions for disease control and prevention and cancer-related learned societies in many countries recommend prioritizing cancer patients for COVID-19 vaccines. All the COVID-19 vaccines currently approved for emergency use, including inactivated vaccines, mRNA vaccines, recombinant adenovirus vector-based vaccines, and recombinant protein subunit vaccines, can be applied in cancer patients. Cancer patients with stable disease can be vaccinated against COVID-19 at any time, while patients with advanced-stage cancer or undergoing anticancer therapy should decide on the timing of vaccination according to the specific situation such as treatment methods and cancer type, etc.. The benefits of COVID-19 vaccination in cancer patients may outweigh the risks, but the immune response rate may be lower in cancer patients, especially in patients with haematological malignancies, than in healthy individuals.Copyright © 2021 by the Chinese Medical Association.
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In recent years, international crude oil prices have been subject to unusually high fluctuations due to the ravages of the COVID-19 epidemic. Under such extreme market conditions, online investor sentiment can strengthen the correlation between oil price changes and external events. We use a (rolling-window) structural vector autoregression method to investigate the dynamic impact of online investor sentiment on WTI crude oil prices before and after the COVID-19 pandemic across multiple topics of price, supply, demand, and so on, which aims to explore the fluctuation mechanism driven by sentiment and the price changes triggered by public health events. The proposed aspect-level sentiment analysis approach can effectively distinguish and measure sentiment scores of different aspects of the oil market. Our results show that the constructed oil price prosperity index contributes 49.84% to the long-term fluctuations of WTI oil price, ranking first among the influencing factors considered. In addition, the peak value of impulse shocks to WTI oil prices rose from 6.47% to 8.40% during the period of dramatic price volatility caused by the epidemic. The results sketch the mechanisms by which investor sentiment can affect crude oil prices, which help policymakers and investors protect against extreme risks in the oil market. © 2023 Elsevier Ltd
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New Engineering Education (NEE) has become increasingly important in higher education in China. The COVID-19 pandemic has forced higher education institutions to adopt online and hybrid modes of instruction globally, with Massive Open Online Courses (MOOCs) becoming a primary educational tool. In this paper, we explore the impacts of online/hybrid modes on NEE courses in the context of the COVID-19 pandemic. We hypothesized that the rapid transition to online/hybrid modes may have negatively affected students due to insufficient preparation by teachers. This hypothesis was tested through an investigation involving 787 students conducted in 2020 and 2021. The results indicated that, while most students considered online/hybrid modes a helpful tool for their studies, 28.69–36.74% of participants reported significant issues. Through one-to-one interviews with negative/neutral attitude students, we found that insufficient and burdensome communication/interaction with classmates and teachers was the main contributor to these issues. We conclude by proposing a conceptual path to address the issues raised in the study, as well as offering the obtained results as a critical reference for educational researchers seeking to improve the quality of online/hybrid courses and contribute to the field of education. © 2023 by the authors.
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COVID-19, the disease caused by SARS-CoV-2, emerged in December 2019 in Wuhan, China, when Chinese authorities confirmed several patients with fever, difficulty breathing, and invasive lesions on the lungs. The virus then spread quickly across the globe, and by May 17, there were a total of 18,151,717 cases worldwide. While some countries still have an exponentially increasing rate of new cases, China has stabilized the spread of the virus. In the review of COVID-19 in this paper, we used sources from Google Scholar, PubMed, Research Gate, etc. In addition, when investigating public policy data and the number of infections, we also used the statements and relevant data from the official websites of the governments of Dalian and Beijing. Our investigation is based on the summary and analysis of the above data to reach our conclusion. We investigated the basic characteristics of COVID-19, the corresponding Sinovac vaccine and mRNA vaccine, the first round of outbreaks in Wuhan, Beijing, and Dalian, and the warning role of COVID-19 in the future. We demonstrated that keeping social distance and isolating infected patients in time can effectively block the transmission of the virus. This paper exposes the necessary public health measures during the pandemic, providing experiences and lessons for a potential future pandemic. © The Authors, published by EDP Sciences.
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Objective To systematically review the efficacy and safety of traditional Chinese medicine (TCM) and antiviral antibody therapy in the treatment of COVID-19. Methods PubMed, EMbase, The Cochrane Library, Web of Science, CNKI, WanFang Data, VIP and SinoMED databases were electronically searched to collect randomized controlled trials (RCTs) on efficacy and safety of traditional Chinese medicine and antiviral antibody therapies for COVID-19 from inception to June 2022. Two reviewers independently screened literature, extracted data and assessed the risk of bias of included studies;then, network meta-analysis was performed by using Stata 14.0 software. Results A total of 44 RCTs were included. The results of network meta-analysis showed that, for mortality rate, the rank of cumulative probability was: TCM+ standard care (SC) (100%)>convalescent plasma (CP)+SC (42%)>SC (8%). In terms of hospital stay time, the rank of cumulative probability was: TCM+SC (95.5%)>SC (31.4%)>CP+SC (23.2%). In terms of time to viral clearance, the rank of cumulative probability was: TCM+SC (97.4%)>SC (37.4%)>CP+SC (15.2%). In the aspect of mechanical ventilation rate, the rank of cumulative probability was: TCM+SC (98.9%)>CP+SC (42.9%)>SC (8.3%). In the aspect of adverse reactions/events, the rank of cumulative probability was: TCM+SC (99.9%)>SC (47.9%)>CP+SC (2.2%). Conclusion The current evidence shows that TCM combined with SC is the most effective treatment in reducing mortality, shortening hospitalization time and viral negative conversion time, reducing mechanical ventilation rate, and the incidence of adverse reactions/events is low. Due to limited quality and quantity of the included studies, more high quality studies are needed to verify above conclusion. Copyright © 2022 West China University of Medical Science. All rights reserved.
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This paper explores multi-person pose estimation for reducing the risk of airborne pathogens. The recent COVID-19 pandemic highlights these risks in a globally connected world. We developed several techniques which analyse CCTV inputs for crowd analysis. The framework utilised automated homography from pose feature positions to determine interpersonal distance. It also incorporates mask detection by using pose features for an image classification pipeline. A further model predicts the behaviour of each person by using their estimated pose features. We combine the models to assess transmission risk based on recent scientific literature. A custom dashboard displays a risk density heat-map in real time. This system could improve public space management and reduce transmission in future pandemics. This context agnostic system and has many applications for other crowd monitoring problems. © 2022 IEEE.
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Remote meetings have become more prevalent due to the COVID-19 pandemic and technology that facilitates remote work. There is limited research on the effect of remote meetings on group performance and the goal of this study is to identify how distractions affect the individual and group creativity in remote work meetings. A virtual study was conducted where groups of four people participated in divergent and convergent thinking tasks. One group member was assigned an additional non-meeting task while another was assigned as a scribe. Measures of creative performance (e.g., uniqueness of idea) of the distracted members and the group were analyzed. The results show that the distractee contributed (on average) less time and ideas when compared to monotaskers and those assigned as a scribe. The study highlights ways that remote meetings can facilitate creativity. © 2022 ACM.
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Objective To explore the application and safety of apheresis technology in collection of Coronavirus Disease 2019 (COVID-19) convalescent plasma (CP), and to analyze the quality characteristics of the plasma. Methods The general data of COVID-19 convalescent plasma (CP) donors, including gender, age, date of discharge or release from medical isolation, were collected based on informed consent. After physical examination, the CP was collected by apheresis technology with plasma separator, inactivated with methylene blue, and determined for severe acute respiratory symptom Coronavirus 2 (SARS-CoV-2) nucleic acid and specific antibody (RBD-IgG) against SARS-CoV-2. Results The collection process went well, and no serious adverse events related to plasma collection were reported during or after the collection. The average age of COVID-19 CP donors was 38 years (n = 933). The distributions of blood groups A, B, AB and 0 in RhD (+) COVID-19 CP were 33. 4%, 29. 2%, 10% and 27. 2% respectively. The plasma donation date was 18 d from the discharge date in average. All the test results of SARS-CoV-2 nucleic acid in CP were negative, while the proportion of plasma samples at SARS-CoV-2 antibody titer of more than 1: 160 was 92. 60%. Conclusion Apheresis technology was safe and reliable. The COVID-19 CP contained high titer antibody. Large-scale collection and preparation of inactivated plasma against SARS-CoV-2 played an important role in the treatment of COVID-19.
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We analyzed the economic benefits versus safety risks of sharing anti-vascular endothelial growth factor (VEGF) vials during the coronavirus disease (COVID-19) pandemic. This single-center retrospective study analyzed the data of patients with neovascular age-related macular degeneration (nAMD), proliferative diabetic retinopathy (PDR) and retinal vein occlusion (RVO) who received anti-VEGF between January 2016 and July 2021 at Renmin Hospital, Wuhan University, China. Costs were compared of the two protocols of intravitreal injections (IVIs) of ranibizumab, aflibercept and conbercept after (i) splitting the vial content for use in two patients and after (ii) disposal of the remaining vial content after use in a single patient, with the COVID-19 outbreak considered as the demarcation point. The incidence rates of post-injection endophthalmitis (PIE) preand post-outbreak were analyzed. The mean cost of a single IVI increased by 33.3%, from 3917.67±71.69 to 5222.67±84.98 Chinese Yuan during the pandemic. The incidences of IVI-related culture-positive PIE were 0.0134% (3 in 22448) and 0.0223% (1 in 4479), respectively, before and after the pandemic (P=0.6532). We conclude that vial sharing of IVIs in a large clinical institution is not associated with increased PIE risk and can significantly reduce the cost of therapy. © 2022
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Several problems were found in the attempt and practice of bilingual teaching in Food safety, mainly including inconsistent foreign language quality of students, messy textbooks and teaching content, inadequate bilingual ability of teachers and lack of supervision of English auxiliary teachers, lack of online network construction, and single teaching methods and other issues. Through summing up experience, it is found that a series of methods, such as combining social hot spots and conducting scientific research hot spots introduction teaching, rationally using English textbooks and correspondingly constructing teaching content, can solve the above problems and promote English teaching of Food safety. During pandemic (COVID-19/Corona Virus Disease 2019) period, we boldly carried out bilingual and online teaching attempts, this time also carried out a summary, hoping to provide some guidance for the teaching reform of Food safety © 2022 IEEE.
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In the early stage of covid-19 disease transmission, it is easy to lead to public panic and dissatisfaction without timely information feedback. In order to solve this problem, this paper constructs an emotion classification and prediction algorithm based on Bayesian network reasoning by analyzing the variable elimination algorithm, connection tree reasoning algorithm and Gibbs sampling algorithm in Bayesian network reasoning algorithm. The algorithm can quickly identify the emotions of Internet users from the communication with low computational resources, and provide reference for the relevant departments to formulate the correct public opinion guidance strategy. © 2021 IEEE.
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This paper aims to solve an optimization problem in the UAV-enabled COVID-19 test kits delivery system. The UAV intends to find the optimal path to deliver the COVID-19 test kits to people with a high probability of COVID-19 infection in the shortest time. The traditional Deep Reinforcement Learning doesn't perform well in solving the optimization problem because of the slow converging speed and difficult parameters-tuning. In order to solve this problem efficiently, a low-complexity Hybrid Reinforcement Learning is proposed. The algorithm consists of a heuristic algorithm and a Q Learning algorithm. At first, a heuristic algorithm is utilized to calculate the optimal path between any two users. Next, Q learning is applied to determine the sequence of the users to deliver the COVID-19 test kits. As a result, both the delivery sequence and the specific path from one user to another can be generated. The simulation results prove the superiority of the proposed Hybrid Reinforcement Learning in solving the proposed optimization problem compared with the state-of-arts. © 2022 IEEE.
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Inhibition of vascular endothelial growth factor (VEGF) has been widely applied in anti-neovascularization therapies. As a novel anti-VEGF agent, KH902 (conbercept) is designed to restrain pathological angiogenesis. However, the effects of KH902 on retinal hypoxia have not been well studied. In a mouse model of oxygen-induced retinopathy (OIR), we assessed retinal hypoxia at postnatal days 14 (P14) and P17, as well as retinal neovascularization (RNV) at P17. In addition, we evaluated the protein level of VEGF and galectin-1 (Gal-1). Changes of the neuroretinal structure were also examined. Our results indicated that KH902 could remit retinal hypoxia in OIR at P14 and P17, which was an exciting novel finding for KH902 function. Additionally, we confirmed that KH902 markedly reduces RNV. Our results indicated that administration of KH902 downregulated VEGF expression, as well as Gal-1. Damage of neuroretinal structure after KH902 injection was not observed, which was also an encouraging result. Our study suggests that KH902 plays a role in alleviating retinal hypoxia and that it could be used for the treatment of other ncovascular ocular diseases.
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In this paper, we use delay differential equations to propose a mathematical model for COVID-19 therapy with both defective interfering particles and artificial antibodies. For this model, the basic reproduction number R-0 is given and its threshold properties are discussed. When R-0 < 1, the disease-free equilibrium E-0 is globally asymptotically stable. When R-0 > 1, E-0 becomes unstable and the infectious equilibrium without defective interfering particles E-1 comes into existence. There exists a positive constant R-1 such that E-1 is globally asymptotically stable when R-1 < 1 < R-0. Further, when R-1 > 1, E-1 loses its stability and infectious equilibrium with defective interfering particles E-2 occurs. There exists a constant R-2 such that E-2 is asymptotically stable without time delay if 1 < R-1 < R-0 < R-2 and it loses its stability via Hopf bifurcation as the time delay increases. Numerical simulation is also presented to demonstrate the applicability of the theoretical predictions.
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Purpose: COVID-19, a causative agent of the potentially fatal disease, has raised great global public health concern. Information spreading on the COVID-19 outbreak can strongly influence people behaviour in social media. This paper aims to question of information spreading on COVID-19 outbreak are addressed with a massive data analysis on Twitter from a multidimensional perspective. Design/methodology/approach: The evolutionary trend of user interaction and the network structure is analysed by social network analysis. A differential assessment on the topics evolving is provided by the method of text clustering. Visualization is further used to show different characteristics of user interaction networks and public opinion in different periods. Findings: Information spreading in social media emerges from different characteristics during various periods. User interaction demonstrates multidimensional cross relations. The results interpret how people express their thoughts and detect topics people are most discussing in social media. Research limitations/implications: This study is mainly limited by the size of the data sets and the unicity of the social media. It is challenging to expand the data sets and choose multiple social media to cross-validate the findings of this study. Originality/value: This paper aims to find the evolutionary trend of information spreading on the COVID-19 outbreak in social media, including user interaction and topical issues. The findings are of great importance to help government and related regulatory units to manage the dissemination of information on emergencies, in terms of early detection and prevention. © 2021, Emerald Publishing Limited.
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In this paper, we use ordinary differential equations to propose a mathematical model for COVID-19 therapy with both defective interfering particles and artificial antibodies. For this model, the basic reproduction number R0 is given and its threshold properties are discussed. We investigate the global asymptotic stability of disease-free equilibrium E0 and infection equilibrium without defective interfering particles E1 by utilizing Lyapunov function and LaSalle’s invariance principle. For infection equilibrium with defective interfering particles E2, stability and Hopf bifurcation results are presented. Numerical simulation is also given to demonstrate the applicability of the the-oretical predictions. © 2021, Wilmington Scientific Publisher. All rights reserved.
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In less than three decades, China has emerged as the world's largest exporting nation with more than 2 trillion exports annually. China's quick rise as a leading exporter in the world is an unprecedented miracle. There are many theories explaining this miracle. This book adopts the global value chain (GVC) approach to analyze the Chinese export miracle over the last four decades. It focuses on the tasks rather than the gross export value and emphasizes the organizations of modern trade rather than the national comparative advantage. The GVC approach systematically explains how, in less than four decades China has evolved from a closed economy to the world's No. 1 exporting nation;why China, a developing country, has exported more high-technology products than labor-intensive products to the US;and why almost half of the US trade deficit has originated from China. The book identifies three spillover effects of GVCs that originated from brands, technology and product innovation, and distribution and retail networks of GVCs lead firms. It argues that China's deep integration with GVCs has been a decisive factor for China's emergence as the world's No.1 exporting nation and the champion of high-technology exports. In addition, this book uses iPhone trade and the operation of Apple, the largest factory-less American manufacturer, to explain how current trade statistics exaggerate China's exports to and its trade surplus with the US on the one hand, and underestimate US exports on the other hand. By using the experience of the Chinese mobile phone industry, the book argues that the GVC strategy can be a short-cut for developing countries to achieve industrialization and enable firms of developing countries to enter high-technology sectors despite their intrinsic disadvantages. At this end, the book also discusses the future trajectory of China-centered GVCs under the shadow of the US-China trade war and the COVID-19 pandemic. © 2021 by World Scientific Publishing Co. Pte. Ltd. All rights reserved.
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Patients with cancer are at high risk for coronavirus disease 2019 (COVID-19). Institutions for disease control and prevention and cancer-related learned societies in many countries recommend prioritizing cancer patients for COVID-19 vaccines. All the COVID-19 vaccines currently approved for emergency use, including inactivated vaccines, mRNA vaccines, recombinant adenovirus vector-based vaccines, and recombinant protein subunit vaccines, can be applied in cancer patients. Cancer patients with stable disease can be vaccinated against COVID-19 at any time, while patients with advanced-stage cancer or undergoing anticancer therapy should decide on the timing of vaccination according to the specific situation such as treatment methods and cancer type, etc.. The benefits of COVID-19 vaccination in cancer patients may outweigh the risks, but the immune response rate may be lower in cancer patients, especially in patients with haematological malignancies, than in healthy individuals. Copyright © 2021 by the Chinese Medical Association.